Using logic to formalize common sense was the topic of one of the first AI documents ever written (McCarthy 1959), and we now have over 45 years of progress to look back on. The view is not encouraging. We are still struggling to handle problems which young children find so trivial as to be below the horizon of conscious effort; and yet computers now routinely play superb chess, recognize faces, control spacecraft and solve challenging industrial-scale problems. AI is doing well, but "logical common sense" is stuck, I suggest, in a dead end, where progress is essentially stymied by old problems that should have been treated as warnings rather than as posing research goals to be solved. This paper attempts to diagnose what went wrong, and suggest some alternative ways in which the field might make better progress.